On 10/09/2013 11:36 AM, Olivier Grisel wrote: > Peter implemented "penalized SVD" with SGD for "Netflix > challenge"-style matrix factorization problems: > > http://code.google.com/p/pyrsvd/ > > It should be a pretty good baseline to compare performance against. > > As for missing data, I would just use scipy.sparse matrices and treat > non-materialized zeros as missing data for the sake of memory > efficiency and API simplicity. > I remember there was a thread on how to encode missing values, I think for the imputation PR. There were three possible scenarios of how to use the sparse matrix structure. Does anyone have a link? I thought the recommendation system API was also discussed there.
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